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Anti-Surveillance Coalition of Long Beach, CA

We are a coalition of Long Beach residents & organizations fighting to see a surveillance-free Long Beach, where we are free to live, love, and express ourselves without the danger of incarceration or deportation. Police surveillance forces us to live under those threats and puts us all in danger. Police don’t keep us safe; they use violence in place of care, and their ability to surveil us increases their power to inflict violence. We don’t want more rules for the police to break or riddle with exceptions – we want to take their spy technology away. Our coalition does not believe in a softer, kinder way of being policed or surveilled; we simply want to live free of it.

Contact Us

Contact us at the Anti-Surveillance Coalition.

Virtual Teach-Ins

The Anti-Surveillance Coalition held an online Community Teach-in on May 4th. 

Save the date for the next Teach-In on Thursday, June 22, 2023 from 6pm – 7:30pm.

Stay connected for updates and future events.

Why Now & Why Long Beach?

The Long Beach Police Department’s (LBPD) ability to spy and track people has grown over the past several years, as the City continues to pour millions of dollars into invasive, shadowy, privately-controlled surveillance technology. While LBPD employs several other invasive spy tools, including thermal imaging cameras and cell phone interception and hacking technologies, we are beginning by focusing on automated license plate reader (ALPR) and facial recognition technology, because we believe these have the broadest impact, and LBPD already has a record of abusing these technologies, with the potential to abuse them even further. 

What are Automated License Plate Readers?

An automated license plate reader (ALPR) is a camera or set of cameras (mobile or stationary) that captures images of license plates and then uploads them and their exact geolocation to a database, where software checks them against “hot lists” of license plates that law enforcement are seeking, usually in order to locate an individual for arrest. The system LBPD uses uploads thousands of images a minute, 99.97% of which have no connection to any investigation. The technology gives law enforcement agencies the power to track people’s movements nearly in real-time.

What is facial recognition?

Facial recognition technology usually takes the form of an artificial intelligence learning to map people’s faces into a series of individual, unique data points. The technology can then compare a given image to others in a database, or, sometimes, to every other publicly available image on the internet and identify matches. The technology incorporates the racial biases of its primarily white male creators, and has higher error rates for people of color and women, leading to several erroneous arrests. Moreover, once a person’s facemap is in the database, that person’s privacy is forever compromised, as we cannot change our faces. 

LBPD shared data it collected from automated license plate readers (ALPRs) with ICE, a practice that only came to light in 2020. Although LBPD claims that they have stopped this data-sharing,  they continue to use the same technology and the same company to store and analyze it: Vigilant Solutions. LBPD also uses facial recognition technology and got caught exploiting the technology to track protesters involved in the 2020 uprisings following George Floyd’s murder. LBPD has not put in place policies that will hold officers accountable for misuse. Even if they did, why should we trust them? LBPD, one of the most violent police departments in the U.S., does not have the confidence of the community to undertake their basic functions, let alone have the power to track our every movement and identify us in every public space.

Long Beach residents’ safety and privacy are at stake, and the City must act urgently to protect Long Beach residents from an unaccountable and powerful Long Beach Police Department and the digital dragnets it has created. The City must ban the use of both ALPR and facial recognition now!

About the Logo

Logo by Christopher Diaz

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